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Optimizing high-degree of freedom robotic manipulators requires searching complex, high-dimensional configuration spaces, a task that is computationally challenging for classical methods. This paper introduces a quantum native framework…

Robotics · Computer Science 2025-10-30 Hassen Nigatu , Shi Gaokun , Li Jituo , Wang Jin , Lu Guodong , Howard Li

We present a generic C++ design to perform efficient and exact geometric computations using lazy evaluations. Exact geometric computations are critical for the robustness of geometric algorithms. Their efficiency is also critical for most…

Computational Geometry · Computer Science 2007-05-23 Sylvain Pion , Andreas Fabri

The set theory relations \in, \backslash, \Delta, \cap, and \cup have corollaries in subspace relations. Geometric Algebra is introduced as the ideal framework to explore these subspace operations. The relations \in, \backslash, and \Delta…

Rings and Algebras · Mathematics 2007-05-23 T. A. Bouma , L. Dorst , H. G. J. Pijls

Robotic manipulation of unfamiliar objects in new environments is challenging and requires extensive training or laborious pre-programming. We propose a new skill transfer framework, which enables a robot to transfer complex object…

A new simplified approach for teaching electromagnetism is presented using the formalism of geometric algebra (GA) which does not require vector calculus or tensor index notation, thus producing a much more accessible presentation for…

Physics Education · Physics 2010-11-11 James M. Chappell , Azhar Iqbal , Derek Abbott

Clifford algebras have broad applications in science and engineering. The use of Clifford algebras can be further promoted in these fields by availability of computational tools that automate tedious routine calculations. We offer an…

Symbolic Computation · Computer Science 2016-05-23 Dimiter Prodanov , Viktor T. Toth

We introduce randomized algorithms to Clifford's Geometric Algebra, generalizing randomized linear algebra to hypercomplex vector spaces. This novel approach has many implications in machine learning, including training neural networks to…

Machine Learning · Computer Science 2024-06-11 Yifei Wang , Sungyoon Kim , Paul Chu , Indu Subramaniam , Mert Pilanci

This paper investigates the development and optimization of control algorithms for mobile robotics, with a keen focus on their implementation in Field-Programmable Gate Arrays (FPGAs). It delves into both classical control approaches such…

Robotics · Computer Science 2024-03-15 Andrés-David Suárez-Gómez , Andres A. Hernandez Ortega

Optimal control problems are formulated and efficient computational procedures are proposed for combined orbital and rotational maneuvers of a rigid body in three dimensions. The rigid body is assumed to act under the influence of forces…

Optimization and Control · Mathematics 2016-11-15 Taeyoung Lee , N. Harris McClamroch , Melvin Leok

As dynamic and control systems become more complex, relying purely on numerical computations for systems analysis and design might become extremely expensive or totally infeasible. Computer algebra can act as an enabler for analysis and…

Systems and Control · Computer Science 2018-01-01 Masoud Abbaszadeh

We survey the main numerical techniques for finite-dimensional nonlinear optimal control. The chapter is written as a guide to practitioners who wish to get rapidly acquainted with the main numerical methods used to efficiently solve an…

Optimization and Control · Mathematics 2022-12-07 Jean-Baptiste Caillau , Roberto Ferretti , Emmanuel Trélat , Hasnaa Zidani

Recent work has shown that complex manipulation skills, such as pushing or pouring, can be learned through state-of-the-art learning based techniques, such as Reinforcement Learning (RL). However, these methods often have high…

We introduce an algorithm which can be directly used to feasible and optimum search in linear programming. Starting from an initial point the algorithm iteratively moves a point in a direction to resolve the violated constraints. At the…

Optimization and Control · Mathematics 2023-12-05 Denys Shcherbak , Natalya Pya Arnqvist

Conformal Geometric Algebra (CGA) is a framework that allows the representation of objects, such as points, planes and spheres, and deformations, such as translations, rotations and dilations as uniform vectors, called multivectors. In this…

Graphics · Computer Science 2021-05-20 Manos Kamarianakis , George Papagiannakis

Researchers working with mathematical models are often confronted by the related problems of parameter estimation, model validation, and model selection. These are all optimization problems, well-known to be challenging due to…

Quantitative Methods · Quantitative Biology 2016-04-04 Elizabeth Gross , Brent Davis , Kenneth L. Ho , Daniel J. Bates , Heather A. Harrington

We present a method for nonlinear parametric optimization based on algebraic geometry. The problem to be studied, which arises in optimal control, is to minimize a polynomial function with parameters subject to semialgebraic constraints.…

Optimization and Control · Mathematics 2007-05-23 Ioannis A. Fotiou , Philipp Rostalski , Bernd Sturmfels , Manfred Morari

Many statistical models are algebraic in that they are defined by polynomial constraints or by parameterizations that are polynomial or rational maps. This opens the door for tools from computational algebraic geometry. These tools can be…

Statistics Theory · Mathematics 2007-06-13 Mathias Drton

Robots exhibit a rich variety of symmetries arising from their mechanical structure and the properties of their tasks. Although many robotics problems exhibit several symmetries simultaneously, existing approaches typically treat them in…

Robotics · Computer Science 2026-05-22 Loizos Hadjiloizou , Rodrigo Pérez-Dattari , Noémie Jaquier

A tutorial introduction to projective geometric algebra (PGA), a modern, coordinate-free framework for doing euclidean geometry. PGA features: uniform representation of points, lines, and planes; robust, parallel-safe join and meet…

General Mathematics · Mathematics 2020-08-19 Charles G. Gunn

Geometric programming is an important class of optimization problems that enable practitioners to model a large variety of real-world applications, mostly in the field of engineering design. In many real life optimization problem…

Numerical Analysis · Computer Science 2011-02-19 A. K. Ojha , K. K. Biswal